Modeling Socially Intelligent Agents

An approach to modeling boundedly rational agents is described. This approach uses the parallel evolution of a population of mental models for each agent based on the genetic programming paradigm. Then some of the characteristics one would expect of a society of agents (as opposed to a collection of interacting agents) is argued for. These include the ability to identify, model, and communicate with specific other agents in a heterogeneous way. An example model is described, which extends Brian Arthurs' “El Farol Bar” model with learning and communication. The model allows the co-evolution of the agents' populations of models. The results are then analyzed to show the differentiation that results between the agents. A specific case study of the situation at the end of the simulation is then examined in depth. This indicates that some of the problems in analyzing human communication will also occur with such models and that explanations based on Wittgensteinian language games and use in practice may be mos...

[1]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[2]  Eizo Akiyama,et al.  Evolution of Cooperation, Differentiation, Complexity, and Diversity in an Iterated Three-Person Game , 1995, Artificial Life.

[3]  Bruce Edmonds,et al.  Modelling Economic Learning as Modelling , 1998 .

[4]  B. Edmonds.  Modelling Bounded Rationality in Agent-Based Simulations Using the Evolution of Mental Models , 1999 .

[5]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[6]  Abraham Kandel,et al.  Compression and Expansion of Fuzzy Rule Bases by Using Crisp-fuzzy Neural Networks , 1998, Cybern. Syst..

[7]  Kaneko,et al.  Globally coupled chaos violates the law of large numbers but not the central-limit theorem. , 1990, Physical review letters.

[8]  Bruce Edmonds,et al.  Modelling Bounded Rationality Using Evolutionary Techniques , 1997, Evolutionary Computing, AISB Workshop.

[9]  Scott Moss,et al.  Boundedly versus Procedurally Rational Expectations , 1999 .

[10]  P. Johnson-Laird.  Mental models , 1989 .

[11]  G. P. Feeley.  Montana , 1897, The Journal of comparative medicine and veterinary archives.

[12]  David J. Montana,et al.  Strongly Typed Genetic Programming , 1995, Evolutionary Computation.

[13]  R. Palmer,et al.  Artificial economic life: a simple model of a stockmarket , 1994 .

[14]  N. Luhmann.  Soziale Systeme : Grundriß einer allgemeinen Theorie , 1984 .

[15]  H. Simon,et al.  Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. , 1959 .

[16]  E. Penrose.  The theory of the growth of the firm twenty-five years after , 1960 .

[17]  A. Koller,et al.  Speech Acts: An Essay in the Philosophy of Language , 1969 .

[18]  Ralph Pettman,et al.  Systems and Cybernetics , 1975 .

[19]  Richard P. Cooper,et al.  A Systematic Methodology for Cognitive Modelling , 1996, Artif. Intell..

[20]  R. Carneiro.  The Evolution of Complexity in Human Societies and Its Mathematical Expression , 1987 .

[21]  Andrzej Nowak,et al.  Measuring emergent social phenomena: Dynamism, polarization, and clustering as order parameters of social systems , 1994 .

[22]  Daniel C. Dennett,et al.  Precis of Consciousness Explained@@@Consciousness Explained. , 1993 .

[23]  Scott Moss,et al.  Modelling the Process of Market Emergence , 1995 .

[24]  Bruce Edmonds,et al.  Logic, Reasoning and A Programming Language for Simulating Economic and Business Processes with Artificially Intelligent Agents , 1996 .

[25]  Pc Earley,et al.  Cross-level analysis of organizations: Social resource management model , 1993 .

[26]  D. Campbell.  Blind variation and selective retention in creative thought as in other knowledge processes. , 1960, Psychological review.

[27]  Eduardo Zambrano.  The Revelation Principle of Bounded Rationality , 1997 .

[28]  Bruce Edmonds,et al.  Modeling Economic Learning as Modeling , 1998, Cybern. Syst..

[29]  W. Arthur.  Inductive Reasoning and Bounded Rationality , 1994 .

[30]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[31]  John BednarzJr.,et al.  Complexity and intersubjectivity: Towards the theory of Niklas Luhmann , 1984 .

[32]  Jasmina Arifovic.  Genetic algorithm learning and the cobweb model , 1994 .

[33]  Bruce Edmonds,et al.  Validation and Verification of Computational Models with Multiple Cognitive Agents , 1997 .

[34]  Bruce Edmonds,et al.  SDML: A Multi-Agent Language for Organizational Modelling , 1998, Comput. Math. Organ. Theory.